Master Students; m​/f​/d

Your tasks

The candidate will join an interdisciplinary team to perform bioinformatic analyses on brain insulin resistance and the epigenetic regulation of type 2 diabetes subtypes. The master’s project focuses on developing analysis pipelines to extract deeper insights from existing epigenetic and phenotypic datasets.

• Analyze blood DNA methylation from a large cohort
• Apply machine and deep learning methods to build an epigenetic risk score
• Optimize a data-integration pipeline combining epigenetic and proteomic data into a composite score

• Analyze DNA methylation in muscle biopsies
• Integrate methylome and transcriptome data to predict the relationship between DNA methylation and alternative splicing
• Use established clustering methods in the group (PAM and WGCNA)

• Analyze blood DNA methylation in a large cohort
• Integrate clinical and epigenetic data for correlation analyses
• Use machine and deep learning to derive an epigenetic risk score
• Apply PAM and WGCNA for data-driven patient stratification

The student will gain hands-on experience in multi-omics integration (epigenomics, transcriptomics, and clinical data) and advanced bioinformatic methods within a collaborative academic and clinical research environment.

• Bachelor’s degree in bioinformatics, mathematics, statistics, or in a biological science with substantial analytical background knowledge
• Basic skills in Unix operation systems and intrinsic interest in genetics would be an asset

The candidates will enjoy team working and interactions with experimental scientists and other bioinformaticians to work on complex datasets, and will have experience using tools such as R/Bioconductor or python.

Please send your application until latest January 31st, 2026 via E-Mail to .

For further information please do not hesitate to contact:
Dr. Meriem Ouni
Head of the Junior Research Group Epigenetics of Obesity and Diabetes
E-Mail:

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